This is a series of invited colloquiual lectures provided by top researchers in the field of systems biology, theoretical and computational biology, bioinformatics and related fields of applied mathematics and computer science. The series is prepared in collaboration with Global Change Research Centre AS CR as a part of the ESF co-funded project CyanoTeam. The project is associated with an international network CyanoNetwork.

Lectures run irregularly during the academic year with respect to the time schedule provided on this web page. Each of the lectures will be announced at least one week in advance.

Computational modelling of biological machinery in a living cell (e.g., gene regulatory networks or signalling pathways) often leads to dynamical models characterised by huge state spaces of sizes that surpass the sizes of any human-designed systems by orders of magnitude. Therefore, profound understanding of biological processes asks for the development of new methods and tools that would provide means for formal analysis and reasoning about such big systems.

In the first lecture, we consider Probabilistic Boolean Networks (PBNs), a computational framework for the modelling of biological regulatory networks. One of the key aspects in the analysis of PBN models is the comprehension of their long-run (steady-state) behaviour. In particular, we focus on the computation of steady-state probabilities, which, e.g., are crucial for the quantification of the impact of genes on other genes or for the identification of network elements with highest impact. Obtaining the steady-state distribution for large PBNs poses a significant challenge. We discuss the existing solutions and present our approach to this problem.

In the second lecture, we demonstrate our results for a case-study of a large PBN model of apoptosis in hepatocytes. Finally, we consider future perspectives.